An ensemble and cost-sensitive learning-based root cause diagnosis scheme for wireless networks with spatially imbalanced user data distribution
Science China Information Sciences(2024)
Abstract
A novel feature extraction method that can tolerate imbalanced user data is proposed. A cost-sensitive SVM assigns different misclassification costs to faults with different severity levels to optimize the cause diagnosis process. The simulation results demonstrate the effectiveness and superiority of the proposed algorithm.
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